Setting Up Physics Template in Your Simulation Pipeline
I spent roughly three weeks last year debugging a simulation where rigid bodies were passing through soft obstacles at velocities above 40 m/s. The root cause had nothing to do with collision detection and everything to do with how I'd structured my Physics Template. Once I fixed the mass distribution parameters and tightened the solver iterations, the problem vanished. This isn't a new issue - it comes up every time someone copies a template without understanding what each field actually does. A Physics Template is a reusable configuration block that defines how physical objects behave in your simulation environment. It bundles together mass properties, friction coefficients, restitution values, collision masks, solver settings, and gravity responses into a single definable unit that you can apply across multiple objects without re-typing parameters each time. Think of it as a cookie-cutter for physical behavior rather than a single object's settings. Most engines and simulation frameworks ship with a default template that assumes standard terrestrial conditions - Earth gravity, moderate friction ranges, and basic rigid body constraints. That default works fine for prototyping, but production environments almost always require modification. I've seen teams ship projects with default templates because they assumed the defaults would be close enough. They weren't.
Building a Template from Scratch
Start by identifying the object classes you need. A common mistake is creating one monolithic template and trying to force every object to fit. Instead, build separate templates for at least three categories: static geometry, kinematic triggers, and dynamic rigid bodies. Static geometry needs collision volume but zero mass and zero solver participation. Kinematic triggers need active collision testing but no automatic response. Dynamic rigid bodies are where most of your tuning work goes. For each category, set these core parameters first. Mass should reflect actual material density scaled to your object's volume - don't guess at numbers. Friction has two components: static friction (resistance to initial movement) and kinetic friction (resistance during sliding). Restitution controls bounciness and should stay below 0.8 for most realistic materials unless you're simulating something specifically designed to bounce. Collision layers and masks determine which objects interact with which other objects - get this wrong and you'll see objects ignoring collisions entirely or phantom collisions between unrelated items. Solver iterations are where beginners lose track of performance. More iterations mean more accurate physics but higher CPU cost. I recommend starting with 10 iterations for dynamics and 5 for constraints. If objects are still jittering or tunneling after that, increase in increments of 3, not 10. Jumping straight to 30 iterations is a common way to burn through your frame budget.
The Angular Damping Issue
Here's something most documentation glosses over: angular damping behaves completely differently depending on whether your engine integrates rotation using quaternions or Euler angles. If you're using quaternions, angular damping applies a direct scalar reduction to angular velocity each frame. With Euler integration, the damping interacts unpredictably with the object's orientation axis alignment, sometimes causing objects to appear to accelerate rotationally instead of decelerate. I encountered this when a client's spinning door mechanism started rotating faster the longer it spun. Switching to quaternion-based rotation solved it, but the documentation for both approaches claimed identical damping behavior. Another counter-intuitive point: making objects heavier doesn't always solve tunneling. Increasing mass while keeping velocity constant actually makes the problem worse in some engines because the time step resolution stays the same. The effective penetration depth increases with momentum. The real fix is either enabling continuous collision detection (CCD) on fast-moving objects or reducing your fixed time step from the default 1/60 to something like 1/120. CCD adds overhead though - it roughly doubles the collision check cost per object, so apply it selectively only to objects moving faster than your threshold value.
Get the Full Details
Applying and Testing Your Template
Once your template is configured, assign it to objects through your engine's component system or resource pipeline. In Unity-based projects this means creating a ScriptableObject or a prefab with the Physics Template asset applied. In Unreal, you'd use a Physics Asset or material setup. In custom engines, you'll likely have a config file or serialized structure. The assignment method matters less than verifying the template actually propagated correctly - I've lost hours tracing bugs only to discover a template override had been accidentally disabled on a single object in a scene. Testing should follow a specific sequence. Start with a single object in isolation, apply a force, and verify it responds within expected parameters. Then add a second object and watch the interaction. Finally, introduce a third object and check for any unexpected chain reactions or ghost collisions. This progressive complexity reveals template issues that a single-object test would never catch. I set up automated regression tests that run a standard physics scenario before each build - it takes about four minutes and catches roughly 60% of template misconfigurations before they reach QA.
When Physics Template Isn't the Right Answer
There are scenarios where a template-based approach breaks down completely. If you're building a simulation with thousands of interacting soft bodies or fluid dynamics, a rigid body Physics Template won't help and may actively hurt performance by forcing simplified collision shapes onto objects that need volumetric representation. Similarly, procedural physics - where object properties change dynamically based on environmental conditions - requires runtime parameter adjustment rather than static template application. In those cases, consider building a parameter function or expression system instead of a template, even though it requires more upfront development time. The other limitation is cross-engine compatibility. Physics Templates are engine-specific in their underlying data structures. Exporting a template from one engine to another almost always requires manual conversion and validation. There are no reliable universal formats for this. If your project involves multiple engines, plan for template recreation rather than migration. For a working reference implementation, most major engines provide starter templates in their documentation repositories or community asset stores. Look for ones that include the solver configuration details and mass distribution examples - those are the ones that are actually useful rather than just decorative.
